Cutting Force Prediction Models by FEA and RSM When Machining X56 Steel with Single Diamond Grit

At a Glance

Metadata	Details
Publication Date	2021-03-19
Journal	Micromachines
Authors	Lan Zhang, Xianbin Sha, Ming Liu, Liquan Wang, Yongyin Pang
Institutions	Harbin Engineering University
Citations	8
Analysis	Full AI Review Included

Executive Summary

This study utilized Finite Element Analysis (FEA) and Response Surface Methodology (RSM) to develop predictive models for the cutting force generated by a single diamond grit machining X56 pipeline steel.

Core Objective: To establish accurate mathematical models relating cutting force (F) to cutting speed (v), depth of cut (h), and coefficient of friction (µ) for optimizing diamond wire saw operations.
Methodology: 64 virtual experiments (FEA using AdvantEdge) and physical experiments (RSM using a tribometer) were conducted to derive two distinct prediction models.
Key Finding (Significance): Variance analysis (ANOVA) confirmed that the depth of cut (h) is the most significant factor determining the cutting force, followed closely by the coefficient of friction (µ).
Model Accuracy: Both derived models showed high reliability, with prediction errors relative to experimental results ranging from -11.7% to 10.02%, which is acceptable for engineering applications.
Design Implication: High protrusion heights for brazed diamond grits are recommended during manufacturing to enlarge the diamond-workpiece contact area, which helps reduce the coefficient of friction.
Operational Guidance: Cutting speed, while having a minor direct contribution to force, must be restricted to a specified range to effectively reduce the coefficient of friction and mitigate wear.

Technical Specifications

Parameter	Value	Unit	Context
Workpiece Material	X56 Pipeline Steel	N/A	Material used for submarine pipelines.
Tool Material	Polycrystalline Diamond	N/A	Single grit model for simulation.
Grit Prism Length (Modeled)	200	µm	Simplified two-dimensional model dimension.
Cutting Speed Range (v)	960 to 1500	m/min	Range used in FEA and RSM experiments.
Depth of Cut Range (h)	0.01 to 0.04	mm	Range used in FEA and RSM experiments.
Friction Coefficient Range (µ)	0.1 to 0.7	N/A	Range used in FEA and RSM experiments.
FEA Model Constant (k)	79.4941	N/A	Pre-exponential factor in the empirical model.
FEA Model Exponent (v)	-0.0977	N/A	Exponent for cutting speed (v) in the force model.
FEA Model Exponent (h)	0.7145	N/A	Exponent for depth of cut (h) in the force model.
FEA Model Exponent (µ)	0.2020	N/A	Exponent for friction coefficient (µ) in the force model.
RSM Model Accuracy	-9.99 to 10.02	%	Prediction error range compared to experimental data.
FEA Model Accuracy	-11.7 to -6.4	%	Prediction error range compared to experimental data.

Key Methodologies

The study employed a dual-modeling approach using virtual and physical experiments to derive and validate the cutting force prediction equations:

Finite Element Modeling (FEA):
- Software: AdvantEdge was used for 2D machining simulation of the single diamond grit cutting X56 steel.
- Design: 64 virtual experiments were performed by varying cutting speed, depth of cut, and friction coefficient across four levels each.
- Model Derivation: The resulting cutting force data were fitted using least-squares regression to obtain the empirical exponential model: F = 79.4941 * v^-0.0977 * h^0.7145 * µ^0.2020.
Response Surface Methodology (RSM) and Physical Experimentation:
- Equipment: SFT-2M tribometer was used for microcutting experiments on X56 steel sheets.
- Design of Experiments (DoE): A central composite face centered design with three levels for each parameter (speed, depth of cut, friction) and six center points was utilized (20 runs total).
- Model Derivation: ANOVA analysis was performed on the experimental data to identify significant factors and generate a statistical cubic regression model (RSM model).
Model Validation:
- Twelve confirmation experiments were conducted using the SFT-2M tribometer under various parameter combinations.
- Predicted cutting forces from both the FEA-derived model and the RSM model were compared against the measured experimental forces to verify accuracy and reliability.

Commercial Applications

The derived cutting force prediction models and associated findings are crucial for optimizing the performance and longevity of diamond wire saws used in heavy industrial applications.

Subsea Infrastructure Maintenance: Provides the necessary framework for the parametric programming of diamond wire saws used for emergency cutting and removal of X56 steel submarine pipelines.
Diamond Tool Manufacturing Optimization: The emphasis on the depth of cut and friction coefficient directly informs the design of brazed diamond beads, specifically dictating the required protrusion height of the grits to optimize contact mechanics and minimize wear.
Process Efficiency and Tool Life: By understanding the relationship between cutting speed and friction coefficient, operators can restrict speed to a range that reduces friction, thereby mitigating abrasive wear and fatigue failure, extending the service life of the diamond wire.
Advanced Machining Control: The models enable the development of predictive control systems for micro-machining processes, allowing real-time adjustment of parameters to maintain a target cutting force or maximize material removal rate while ensuring tool integrity.

View Original Abstract

In the field of underwater emergency maintenance, submarine pipeline cutting is generally performed by a diamond wire saw. The process, in essence, involves diamond grits distributed on the surface of the beads cutting X56 pipeline steel bit by bit at high speed. To find the effect of the different parameters (cutting speed, coefficient of friction and depth of cut) on cutting force, the finite element (FEA) method and response surface method (RSM) were adopted to obtain cutting force prediction models. The former was based on 64 simulations; the latter was designed according to DoE (Design of Experiments). Confirmation experiments were executed to validate the regression models. The results indicate that most of the prediction errors were within 10%, which were acceptable in engineering. Based on variance analyses of the RSM models, it could be concluded that the depth of the cut played the most important role in determining the cutting force and coefficient the of friction was less influential. Despite making little direct contribution to the cutting force, the cutting speed is not supposed to be high for reducing the coefficient of friction. The cutting force models are instructive in manufacturing the diamond beads by determining the protrusion height of the diamond grits and the future planning of the cutting parameters.

Tech Support

Original Source

DOI: https://doi.org/10.3390/mi12030326

References

2014 - High-Speed Slicing of SiC Ingot by High-Speed Multi Wire Saw [Crossref]
2009 - Research on Experimentation of Diamond Wire Saw Cutting Compound Pipes Underwater [Crossref]
2006 - Machining Performance of Brazed Diamond Wire Saw with Optimum Grain Distribution [Crossref]
2009 - Study on Electroplated Diamond Wire Saw Development and Wire Saw Wear Analysis [Crossref]
2006 - Analysis of the Breakage of Diamond Wire Saws in Sawing of Stone [Crossref]
2001 - A class of slipline field solutions for metal machining with slipping and sticking contact at the chip-tool interface [Crossref]
2011 - Advanced friction modeling for bulk metal forming processes [Crossref]
2011 - Modelling of cutting induced surface phase transformations considering friction effects [Crossref]